MOP-ND 🚴

GR
Gianluca Rea

🚴 Overview

A data analytics project implementing a Multi-commodity Orienteering Problem with Network Design (MOP_ND) for the "Data Analytics and Data Driven Decision" course at the University of L'Aquila.

The project focuses on designing optimal single origin-destination itineraries for several classes of cycle-tourists based on the research paper: "Designing single origin-destination itineraries for several classes of cycle-tourists".

🦾 Repository

See the code: MOP-ND Repository

📊 Project Goal

Solve the multi-commodity orienteering problem which involves:

  • →Designing multiple routes for different tourist classes
  • →Optimizing network design for cycling tourism
  • →Balancing route quality, distance, and tourist preferences
  • →Maximizing tourist satisfaction across multiple itineraries

🛠️ Tech Stack

  • →Python: Core implementation language
  • →Jupyter Notebooks: Interactive analysis and development
  • →Gurobi: Mathematical optimization solver
  • →NumPy: Numerical computations
  • →NetworkX: Network and graph analysis
  • →Matplotlib: Visualization of results and graphs
  • →Itertools: Combinatorial utilities

🧪 Getting Started

Requirements:

  • →Gurobi (optimization solver)
  • →NumPy
  • →NetworkX
  • →Matplotlib
  • →Itertools
  • →Jupyter

The project consists of interactive Jupyter notebooks implementing the algorithm and analyzing results.

📚 Learn More

For more information about the orienteering problem and network design optimization, refer to the academic literature and the implementation notebooks.

🤝 Contributing

Contributions are welcome! If you have a suggestion that would make this better, please fork the repo and create a pull request. Any contributions are greatly appreciated.

  1. →Fork the repository
  2. →Create a feature branch: git checkout -b feature-name
  3. →Commit your changes: git commit -m 'Add new feature'
  4. →Push to the branch: git push origin feature-name
  5. →Open a Pull Request

Please ensure your code follows the existing style and includes appropriate documentation.

📧 Contact

For questions, feedback, or collaboration opportunities, feel free to reach out:

This repository reflects my passion for developing tools that enhance network performance and efficiency. I hope it serves as a useful resource for anyone interested in network monitoring and optimization.